Systems and methods for detecting and identifying arcing based on numerical analysis

ABSTRACT

Method and system allowing more accurate detection and identification of unwanted arcing include novel processing of signal voltage representing recovered power-line current. In one implementation, arc-faults are detected based on numerical analysis where individual cycles of line voltage and current are observed and data collected during each cycle is processed to estimate likelihood of presence of arc-event within each individual cycle based on pre-defined number of arc-events occurring within pre-defined number of contiguous cycles. In another implementation, fast transient current spikes detection can be done by: computing difference values between consecutive line-current samples collected over a cycle, average of differences, and peak-to-peak value of line-current; comparing each difference value to average of difference; comparing each difference value to peak-to-peak value; and, based on calculation of composite of two comparisons, using thresholds to determine if arcing is present within processed cycle.

CROSS-REFERENCE TO RELATED APPLICATION

The present application is a continuation of U.S. Non-Provisionalapplication Ser. No. 16/921,594 filed on Jul. 6, 2020 issued as U.S.Pat. No. 11,355,910, which is a continuation of U.S. Non-Provisionalapplication Ser. No. 16/361,468, filed on Mar. 22, 2019 issued as U.S.Pat. No. 10,707,670, which is a continuation of U.S. of Non-Provisionalapplication Ser. No. 14/675,012, filed on Mar. 31, 2015 issued as U.S.Pat. No. 10,243,343, which claims priority from U.S. ProvisionalApplication No. 61/973,251, filed on Mar. 31, 2014, in the U.S. Patentand Trademark Office, and PCT/US/15/23414 filed Mar. 30, 2015. Thepresent application relates to U.S. Provisional Application No.61/781,553, filed on Mar. 14, 2013, in the U.S. Patent and TrademarkOffice, and to U.S. Non-Provisional application Ser. No. 14/206,093,filed on Mar. 12, 2014 the entire contents of which are herebyincorporated by reference.

FIELD OF THE INVENTION

The present application relates to the detection and identification ofarcing, for example, for use with arc fault circuit interrupters.

BACKGROUND OF THE INVENTION

General Description of Arcing in Air and Solid Materials:

Arcing can occur as a result of electrical wire damage. For example, anail or a screw may puncture insulation or create a small break in aconductor. As a result, an arc can form, and traverse air or punchthrough compromised insulation. While all arcs are generally formed insimilar ways, the electrical characteristics of arcing through air canbe different from those of arcing through carbonized insulation.

An arc is an accelerated electron phenomenon. As an electric fieldincreases, for example due to increasing voltage, electrons typicallybegin to move along the electric field, skipping from one atom toanother. In a solid material, an electron flow over a finite amount oftime can be considered a current. This current may be seen as an arc.Yet, when electrons are stripped from atoms at one end of a solidmaterial, higher electric field strength is typically required to stripan additional electron. The arc path can as a result become unsuitablefor sustaining an arc, forcing the arc to find another path. Over time,a used path can eventually recover, though several other arc paths maybe used before a path or a portion of a path regains its suitability. Inair, a similar phenomenon may occur. Yet, the movement of air can createadditional features of a discharge. For example, “previous path” may notexist in the context of an arc in air, because of the movement of air.Furthermore, even when air is highly confined, it can be heated duringarcing, resulting in substantial turbulence within the space.

Arcs in a solid material tend to break molecular bonds. They canencourage new bonds and new chemical composition in the solid material.In most plastics, for example, an arc can dissociate carbon fromhydrogen. As hydrogen escapes into air, carbon is left in the plastic,usually with a black appearance, in a process often referred to ascarbonization. Since carbon is more conductive than most plastics, areasof carbonization tend to be locations where arcing often recurs. Theseareas are usually in the form of small black pits, rather than largeareas of carbon, which can nevertheless occur in extreme cases.

Although devices exist for detecting arcing in electrical circuits, theytypically face such problems as oversensitive arcing detection orerroneous arcing identification. For example, conventional arc faultcircuit interrupters often trip when detecting arcing due to the normalfunctioning of electrical components such as electric motors, ratherthan when detecting arcing due to electrical wire damage. Therefore,there is a need for a system that allows for more accurate detection andidentification of potentially unwanted arcing with speed and accuracyappropriate for commercial applications.

SUMMARY OF THE INVENTION

Illustrative embodiments of the present invention address at least theabove problems and/or disadvantages, and provide at least the advantagesdescribed below.

Exemplary embodiments of the present invention provide methods ofdetecting and identifying arcing generally based on numerical analysiswhere individual cycles of the line voltage and current are observed.

According to an exemplary embodiment of the present invention,zero-crossings on the rising edge of the voltage waveform are used tomark the beginning of each cycle for the line-current observations. Thedata collected during each cycle is subsequently processed to estimatethe likelihood of the presence of an arc-event within each individualcycle. An arc-fault is determined to be present when a pre-definednumber of arc-events are found to occur within a pre-defined number ofcontiguous cycles.

According to another exemplary embodiment of the present invention,methods and systems are provided where detection of fast transientcurrent spikes can be done by computing difference function values forthe line-current samples as they are collected over a single, forexample 60-Hz, cycle, determine a maximum value and a minimum value ofthe plurality of line current samples for the cycle, calculating apeak-to-peak value of the line-current for the cycle as a relativedifference between the maximum value and the minimum value of theplurality of line current samples, calculating an average of thedifference function values, and comparing each of the differencefunction values to the calculated average of the difference functionvalues and the calculated peak-to-peak value of the line-current for thecycle. According to an exemplary implementation of an embodiment of thepresent invention fast transient current spike in the cycle can beidentified based on a result of at least one of such comparing.

According to yet another embodiment of the present invention, a productof the two comparisons can forms a composite spike detection function ora weighting function that emphasizes difference values that are large incomparison to both the peak-to-peak value of the line-current and theaverage difference of the line-current samples. In an exemplaryimplementation, the weighting function also de-emphasizes differencevalues that are small in comparison to both the peak-to-peak value ofthe line-current as well as the average difference of the line-currentsamples. The weighing function then aids in the identification offast-transient current spikes within a single cycle of the line currentby effectively improving the signal-to-noise ratio of the spikedetector.

According to yet another embodiment of the present invention, based onthe results of the composite comparison function calculation, thresholdscan be used to determine if arcing is present within the processed cycleof current. In an exemplary implementation, two thresholds include adetection value limit threshold above which the result of thecalculation for a given sample point is recognized as a current-spike,and a minimum count threshold setting a minimum required number ofsample points within the cycle for which the result of the calculationexceeds the defined current-spike detection value limit. According to anexemplary implementation, a reliable determination of the presence ofarcing within a given cycle may then be made through the properadjustment of both the detection value limit and minimum countthresholds

BRIEF DESCRIPTION OF THE DRAWINGS

The above and other exemplary features, aspects and advantages of thepresent invention will become more apparent from the following detaileddescription of certain exemplary embodiments thereof when taken inconjunction with the accompanying drawings in which:

FIG. 1 illustrates a block diagram of a circuit for performingpower-line current monitoring and analog pre-processing according to anexemplary embodiment of the present invention;

FIGS. 2A1, 2A2, and 2A3 show an illustrative method of detecting andidentifying arcing according to an exemplary embodiment of the presentinvention;

FIGS. 2B1, 2B2, and 2B3 show an illustrative method of detecting andidentifying arcing according to another exemplary embodiment of thepresent invention; and

FIG. 3 shows an illustrative example of line-current cycles in whicharcing is both present and absent.

FIG. 4 shows an illustrative example of a series arc reference waveformaccording to an exemplary implementation of the present invention.

FIG. 5 shows an illustrative example of an arcing half-cycle referencewaveform according to an exemplary implementation of the presentinvention.

FIG. 6 shows an illustrative example of a waveform representative of afast transient arcing phenomenon.

FIG. 7 shows an illustrative example of a fast transient arc pulsereference waveform according to an exemplary implementation of thepresent invention.

FIG. 8 shows an illustrative example of results of a correlation betweenline-current and arc-pulse reference according to an exemplaryimplementation of the present invention.

FIG. 9 shows another illustrative example of a waveform representativeof a fast transient arcing phenomenon.

FIGS. 10A, 10B, and 10C show a graphic representation of analysesperformed according to an exemplary embodiment of the present inventionin the identification of fast-transient current spikes within a singlecycle of the line current.

FIG. 11 illustrates results of calculations at each sample according toan exemplary embodiment of the present invention.

DETAILED DESCRIPTION OF ILLUSTRATIVE EMBODIMENTS

This description is provided to assist with a comprehensiveunderstanding of illustrative embodiments of the present inventiondescribed with reference to the accompanying drawing figures.Accordingly, those of ordinary skill in the art will recognize thatvarious changes and modifications of the illustrative embodimentsdescribed herein can be made without departing from the scope and spiritof the present invention. Also, descriptions of well-known functions andconstructions are omitted for clarity and conciseness. Likewise, certainnaming conventions, labels and terms as used in the context of thepresent disclosure are, as would be understood by skilled artisans,non-limiting and provided only for illustrative purposes to facilitateunderstanding of certain illustrative implementations of the embodimentsof the present invention.

Generally referring to FIGS. 1-11 , systems and methods can detect andidentify or assist in the detection and identification of arcing.

According to an illustrative embodiment of the present invention,individual cycles of the line voltage and current are observed, and alikelihood of the presence of an arc-event within an individual cycle isestimated based upon the following criteria:

-   -   (1) Correlation of each observed cycle of the current waveform        with a known arc reference cycle.    -   (2) Correlation of each observed cycle of the current waveform        with the preceding observed cycle.    -   (3) Determination of monotonic behavior in the RMS amplitude of        the line-current from observations of the current waveform over        a pre-determined number of cycles.

According to an illustrative embodiment of the present invention,individual cycles of the line voltage and current are observed withreference to zero-crossings on the rising edge of the voltage waveformwhich are used to mark the beginning of each cycle for the line-current.The data collected during each cycle can be subsequently processed toestimate the likelihood of the presence of an arc-event within eachindividual cycle. For example, an arc-fault is determined to be presentwhen a pre-defined number of arc-events are found to occur within apre-defined number of contiguous cycles.

In an illustrative embodiments of the present invention, using first (1)criterion, a single known arc reference cycle is produced throughobservation of the current while arc events are generated in acontrolled fashion under a multitude of conditions, for example such asthose specified in Standards documents such as UL1699. The known arcreference cycle can be determined from the observations as thenormalized average expected wave-shape of a single cycle of current inwhich an arc is present. Observations of the line current cycle arecorrelated with the known arc reference in order to estimate thelikelihood that an arc-event is present within the observed cycle.

In general, current waveform produced by some electrical equipment, suchas for example an electronic lamp dimmer controlling an incandescentlight-bulb, can mimic a signature waveform of an arc-event. The observedcurrent from these types of loads can be well correlated with the knownarc reference cycle described for the first (1) criteria and can producea false indication of the presence of an arc-event.

According to an exemplary embodiment of the present invention, in orderto distinguish the current cycles produced by these types of loads fromcycles in which an actual arc-event is present, the second (2) criteriacorrelates an observed cycle of the line current with the precedingobserved cycle. Relative to a true arc-fault condition, electrical loadsthat mimic the signature waveform of an arc-event produce a currentwaveform that is more uniform on a cycle-to-cycle basis when observedover multiple cycles. To the contrary, under a true arc-fault conditionthe resulting current waveform is more random on a cycle-to-cycle basis.The second (2) criterion then estimates the likelihood that an arc-eventidentified by the first criteria is actually an electrical load thatmimics the signature waveform of an arc-event.

There are still other types of electrical equipment that can produce acurrent waveform that mimics the signature waveform of an arc-event, andfor which a given set of cycles will not be well correlated with theirpredecessors when observed over multiple cycles. This type of behaviorcan be observed when the load presented by the equipment varies overtime, for example as is the case with a variable speed drill.Furthermore, it can be observed that these types of varying loadsgenerally produce a monotonic behavior in the root-mean-square (RMS)amplitude of the line current when observed over a pre-determined numberof cycles. To the contrary, the current waveform produced under a truearc-fault condition is generally not monotonic due to the more randomnature of the arc-events that occur during contiguous observations ofthe line-current.

According to an exemplary embodiment of the present invention, anoutcome of the third (3) criterion can be used to adjust the detectionthresholds of the first two, (1) and (2), criteria in order tofacilitate prevention of false detection of an arc-fault under a varyingload condition on the line.

According to an exemplary embodiment of the present invention, anarc-event is determined to be present when a specific combination ofoutcomes occurs in the aforementioned three criteria, (1), (2) and (3),following observation of a single cycle of the current waveform. In anexemplary implementation, an arc-event is determined to be presentduring the cycle when the observations of the current are wellcorrelated to the known arc reference cycle, and are not well correlatedto the observations taken during the preceding cycle.

In an exemplary implementation of the embodiments of the presentinvention, thresholds that are used to gauge the degree of correlationrequired for arc-event detection can be specified based upon thedetermination of monotonic behavior in the RMS amplitude of theline-current following observations of the current waveform over apre-determined number of cycles

In an exemplary implementation, an arc-fault can be determined to bepresent when a pre-defined number of arc-events are found to occurwithin a pre-defined number of contiguous cycles. Both the requirednumber of detected arc-events and the number of cycles in theobservation window are determined based on a range classification of theRMS amplitude of each observed cycle of the line-current. For example,range classifications may be extracted from Standards documents such asUL1699 which specifies different arc test clearing times based on thecurrent level being tested, where for example ranges of 0<x<=5 Arms,5<x<=10 Arms, 10<x<20 Arms and 20<x<=30 Arms are specified for an 20 AmpAFCI.

According to an exemplary embodiment of the present invention a sensedcurrent can be processed by electronics of FIG. 1 where current I(t) ispassed through a sensor coil and analog electronics, including forexample, a band-pass filter, an integrator circuit and a scalingcircuit, that condition the sensed current signal prior to handing itoff via an analog to digital converter to, for example a microprocessorexecuting a detection algorithm.

As illustrated in the example of FIG. 1 , power line-current can bemonitored via an air-core Rogowski coil 100 attached around the hot lead108 of an AC circuit 110. The coil produces a voltage that isproportional to the time-derivative of the current flowing in the ACcircuit. In an exemplary implementation, the signal voltage from thecoil is band-pass filtered by a band-pass filter circuit 102 andintegrated by an integrator circuit 104 in order to recover a signalvoltage that is proportional to the current flowing in the AC circuit.In an exemplary implementation, band-pass filter 102, with a 3-dBpass-band between 1-Hz and 8-kHz, attenuates unnecessary low- andhigh-frequency content that might otherwise saturate the integrator 104.In yet another exemplary implementation, a gain stage 106 then scalesthe signal to the full-scale input voltage of the Analog-to-Digital(A/D) converter which will sample the signal for subsequent digitalpost-processing. For example, a 30-Arms line-current may be scaled to afull-scale voltage of 3.0 Vdc at the A/D converter.

According to an exemplary embodiment of the present invention, signalvoltage representing the recovered power-line current can be processedfor arc-detection as conceptually illustrated in FIGS. 2A1, 2A2, 2A3 and2B1, 2B2, 2B3. In an exemplary implementation, requirements for theresponse to and the conditions for recognition of an arc can be obtainedfrom UL standard 1699. For example, the time in which the AFCI has tointerrupt the circuit upon detection of an arc under the variousconditions outlined in UL1699 is dependent upon the RMS amplitude of theline-current present at the time the arc is detected. In an exemplaryimplementation, pursuant to the standard, currents up to 500-Arms arespecified in the conformance tests for certification. In order topreserve the resolution for currents at or below 150% of the 20-Ampcurrent rating of the AFCI while at the same time maintaining theability to handle a 500-Arms full-scale requirement with the availabledynamic range of the 16-bit A/D converter, it is necessary to divide andappropriately scale the monitored current into low- and high-ranges.FIGS. 2A1, 2A2, and 2A3 provide a process flow and component diagram 200according to an exemplary implementation depicting a UL1699 standarddriven arc detection algorithm for currents at or below 30-Arms. FIGS.2B1, 2B2, and 2B3 (where labels for like elements have been omitted forconciseness) provide a process flow and component diagram 300 accordingto an exemplary implementation for currents up to 500-Arms. In a furtherexemplary implementation, the UL1699 standard specifies the recognitionof arcs within half-cycles of the line-current for the conditions inwhich the high-range detection process shown in FIGS. 2B1, 2B2, and 2B3applies, whereas full-cycles of the line-current are evaluated in therecognition of arcs in the low-range of FIGS. 2A1, 2A2, and 2A3.

According to an exemplary implementation, as shown in FIGS. 2A1, 2A2,and 2A3 for low-range line-currents, the signal voltage representing therecovered power-line current is first sampled by an A/D converter 202which produces 16-bit samples at a rate of 48-kSamples/sec. The samplesare then passed into a priority queue 204. The power-line voltage isalso monitored for positive-edge zero-crossings in the voltage waveform.Output of a zero-crossing detector circuit 206 marks the beginning ofeach 60-Hz cycle and is used to synchronize processing of theline-current samples, thereby preserving the relative phase relationshipbetween the monitored line-current and line-voltage on a cycle-to-cyclebasis. Samples of the line-current are stored sequentially in thepriority queue 204, beginning with the first sample taken following thedetection of a zero-crossing event in the line-voltage and ending withthe last sample taken prior to the next zero crossing event. Thecontents of the priority queue represent the most recent cycle of theobserved line current and are latched within a buffer 208 upon detectionof the zero-crossing event in the line voltage. The present contents ofthe buffer 208 are transferred to RMS Estimator 222. Similarly, thepresent contents of the buffer 208 are also transferred to a secondbuffer 210 such that the contents of the second buffer represent theprevious cycle of observed line-current.

Exemplary embodiments of the present invention include inter-cyclecorrelation where the contents of buffers containing samples of the mostrecent and previous cycles of observed line-current are compared viacorrelation by, for example, a correlation estimator 212. The currentflow during an arc-event is expected to be more random than the currentflow under normal operating conditions. For example, under normaloperating steady-state conditions the current waveform is expected toexhibit more uniformity from one cycle to the next than may be observedduring an arc-event. Hence, it is expected that the contents of thebuffers 208 and 210 representing the most recent and previousobservations of the line-current will have a higher degree ofcorrelation on average when arcing is not present than when arcing ispresent. This property is illustrated in the example FIG. 3 which showscaptured line-current in which arcing is present during the first threecycles and absent in the last three.

In an exemplary implementation, correlation between the two sets of dataX and Y can be expressed as the normalized correlation coefficientR(X,Y) as determined from the following equation,

${R( {X,Y} )} = \frac{C( {X,Y} )}{\sqrt{{C( {X,X} )}{C( {Y,Y} )}}}$

where:

-   -   X is the set of data samples representing the most recent        observed cycle of the line-current,    -   Y is the set of data samples representing the previous observed        cycle of the line-current,    -   C(X,Y) is the unbiased estimate of sample covariance between        variables X and Y,    -   C(X,X) is the unbiased estimate of sample covariance of variable        X, and    -   C(Y,Y) is the unbiased estimate of sample covariance of variable        Y.

The unbiased estimates of sample covariance for variables X and Y aredetermined from the equations,

${{C( {X,Y} )} = {\frac{1}{N - 1}{\overset{N}{\sum\limits_{k = 1}}{( {{X(k)} - \overset{\_}{X}} )( {{Y(k)} - \overset{\_}{Y}} )}}}}{{C( {X,X} )} = {\frac{1}{N - 1}{\overset{N}{\sum\limits_{k = 1}}( {{X(k)} - \overset{\_}{X}} )^{2}}}}{{C( {Y,Y} )} = {\frac{1}{N - 1}{\overset{N}{\sum\limits_{k = 1}}( {{Y(k)} - \overset{\_}{Y}} )^{2}}}}$

where,

-   -   X(k) is the kth sample of variable X,    -   X is the expected value of variable X,    -   Y(k) is the kth sample of variable Y,    -   Y is the expected value of variable Y, and    -   N is the minimum of the number of samples taken for variables X        and Y.

According to exemplary embodiments of the present invention, arcreferences 214, 216 can be provided as follows. The contents of thebuffer containing the samples of the most recent cycle of theline-current can be also compared via correlation 218, 202 to multiplesets of reference data that represent a typical cycle of current with anarc present. The sets of arc reference cycle data represent arcing thatoccurs under various conditions, and can be derived empirically frommeasurement data taken while performing tests, for example as describedin UL Standard 1699. Collected data can be reviewed on a cycle-by-cyclebasis and cycles in which arcing is present can be tagged. Each arcreference cycle can then be generated as the composite mean of thetagged cycles. Examples of arc reference cycles are shown in FIGS. 4 and5 .

According to an exemplary implementation, another observable phenomenonin the presence of arcing can be manifested by random appearance of fasttransient current spikes, an example of which is shown in FIG. 6 . Anexample of an arc reference representing such behavior is shown in FIG.7 , which was arrived at through observation and empirical analysis ofdata taken while performing tests as described in UL Standard 1699.Samples of the line-current can be correlated with such an arc-pulsereference once every sampling interval. An example of the results of theper-sample correlation of the line-current data with the arc-pulsereference is shown in FIG. 8 where the line-current is plotted as acontinuous line and the “x” markings indicate the correlationcoefficient value for each sample interval.

FIG. 9 illustrates another example of random appearance of fasttransient current spikes as an observable phenomenon in the presence ofarcing.

According to another exemplary embodiment of the present invention,detection of fast transient current spikes can be done by firstcomputing a difference function for the line-current samples as they arecollected over a single 60-Hz cycle. For example, each entry for thedifference function is calculated by subtracting the value of theprevious line-current sample from the current one. The maximum andminimum values of the line-current are also determined as the samplesare collected, such that the peak-to-peak value of the line-current forthe cycle can be calculated as their relative difference. The average ofthe difference function values is then determined at the end of thecycle, and each of the difference function values is compared to boththe calculated average difference value and to the peak-to-peak value ofthe line-current during the cycle. The two comparison operations aredefined by the equations:

${{S_{1}( X_{n} )} = \frac{❘{X_{n} - X_{({n - 1})}}❘}{\lbrack {{\max(X)} - {\min(X)}} \rbrack}}{{S_{2}( X_{n} )} = \frac{❘{X_{n} - X_{({n - 1})}}❘}{( \frac{1}{N - 1} ){\sum_{k = 2}^{N}( {❘{X_{k} - X_{({k - 1})}}❘} )}}}$

where,

-   -   S₁(X_(n)) is the comparison result of the nth difference value        to the peak-to-peak value of the line-current,    -   S₂(X_(n)) is the comparison result of the nth difference value        to the average difference value,    -   X_(n) is the nth sample of the collected line-current data X,    -   X_((n-1)) is the sample preceding the nth sample of the        collected line-current data X,    -   max(X) is the maximum value of the line-current samples        collected during the single 60-Hz cycle,    -   min(X) is the minimum value of the line-current samples        collected during the single 60-Hz cycle,    -   N is the number of line-current samples collected during the        single 60-Hz cycle.

The product of the two comparisons forms a composite spike detectionfunction defined by the equation,

S ₃(X _(n))=S ₁(X _(n))*S ₂(X _(n))

While either S1 or S2 could be used to identify fast transient currentspikes, their composite forms a weighting function that emphasizesdifference values that are large in comparison to both the peak-to-peakvalue of the line-current and the average difference of the line-currentsamples. Likewise, the weighting function de-emphasizes differencevalues that are small in comparison to both the peak-to-peak value ofthe line-current as well as the average difference of the line-currentsamples. The weighing function then aids in the identification offast-transient current spikes within a single cycle of the line currentby effectively improving the signal-to-noise ratio of the spikedetector. The effect is illustrated in FIGS. 10A, 10B, and 10C, in whichthe normalized results of the comparison calculations for S1, S2, and S3are shown respectively for the fast-transient current spike data shownin FIG. 9 .

The un-scaled result of the S3 composite comparison calculation for thefast-transient data in FIG. 9 is shown in FIG. 11 , with the “x”markings indicating the result of the calculation at each sample point(note that the majority of the “x” markings when plotted appear as athick horizontal line extending along the Time axis at essentially zeroof Detection Value axis). For further illustration, in FIG. 11 theline-current is plotted as a continuous solid line and is scaled to thelimits of the calculated S3 comparison values over the cycle forillustrative purposes.

Based on the results of the S3 composite comparison functioncalculation, thresholds can be used to determine if arcing is presentwithin the processed cycle of current. According to an exemplaryimplementation, two thresholds would be required: one marking thedetection value limit above which the result of the calculation for agiven sample point is recognized as a current-spike, and anotherdefining the minimum required number of sample points within the cyclefor which the result of the calculation exceeds the definedcurrent-spike detection value limit. The detection value limit thresholdis set high enough such that noise that may be present under no-loadconditions does not produce any samples within a given cycle that arerecognized as current-spikes. The minimum count threshold is set highenough to accommodate normal operating conditions in whichcurrent-spikes may be expected to be present. For example, thyristorbased light-dimmers will produce at least two current-spikes during eachcycle as they switch on during both the positive and negative halves ofthe full 60-Hz cycle. A reliable determination of the presence of arcingwithin a given cycle may then be made through the proper adjustment ofboth the detection value limit and minimum count thresholds.

The components of the illustrative devices, systems and methods employedin accordance with the illustrated embodiments of the present invention,for example, as illustrated in FIGS. 1 , 2A1, 2A2, 2A3, 2B1, 2B2, and2B3, can be implemented, at least in part, in digital electroniccircuitry, analog electronic circuitry, or in computer hardware,firmware, software, or in combinations of them. These components can beimplemented, for example, as a computer program product such as acomputer program, program code or computer instructions tangiblyembodied in an information carrier, or in a machine-readable storagedevice, for execution by, or to control the operation of, dataprocessing apparatus such as a programmable processor, a computer, ormultiple computers. Examples of the computer-readable recording mediuminclude, but are not limited to, read-only memory (ROM), random-accessmemory (RAM), CD-ROMs, magnetic tapes, floppy disks, optical datastorage devices. It is envisioned that aspects of the present inventioncan be embodied as carrier waves (such as data transmission through theInternet via wired or wireless transmission paths). A computer programcan be written in any form of programming language, including compiledor interpreted languages, and it can be deployed in any form, includingas a stand-alone program or as a module, component, subroutine, or otherunit suitable for use in a computing environment. A computer program canbe deployed to be executed on one computer or on multiple computers atone site or distributed across multiple sites and interconnected by acommunication network. The computer-readable recording medium can alsobe distributed over network-coupled computer systems so that thecomputer-readable code is stored and executed in a distributed fashion.Also, functional programs, codes, and code segments for accomplishingthe present invention can be easily construed as within the scope of theinvention by programmers skilled in the art to which the presentinvention pertains. Method steps associated with the illustrativeembodiments of the present invention can be performed by one or moreprogrammable processors executing a computer program, code orinstructions to perform functions (e.g., by operating on input dataand/or generating an output). Method steps can also be performed by, andapparatus of the invention can be implemented as, special purpose logiccircuitry, e.g., an FPGA (field programmable gate array) or an ASIC(application-specific integrated circuit).

Processors suitable for the execution of a computer program include, byway of example, both general and special purpose microprocessors, andany one or more processors of any kind of digital computer. Generally, aprocessor will receive instructions and data from a read-only memory ora random access memory or both. The essential elements of a computer area processor for executing instructions and one or more memory devicesfor storing instructions and data. Generally, a computer will alsoinclude, or be operatively coupled to receive data from or transfer datato, or both, one or more mass storage devices for storing data, e.g.,magnetic, magneto-optical disks, or optical disks. Information carrierssuitable for embodying computer program instructions and data includeall forms of non-volatile memory, including by way of example,semiconductor memory devices, e.g., EPROM, EEPROM, and flash memorydevices; magnetic disks, e.g., internal hard disks or removable disks;magneto-optical disks; and CD-ROM and DVD-ROM disks. The processor andthe memory can be supplemented by, or incorporated in special purposelogic circuitry.

The above-presented description and figures are intended by way ofexample only and are not intended to limit the present invention in anyway except as set forth in the following claims. It is particularlynoted that persons skilled in the art can readily combine the varioustechnical aspects of the various elements of the various exemplaryembodiments that have been described above in numerous other ways, allof which are considered to be within the scope of the invention.

The above-described exemplary embodiments of an apparatus, system andmethod in computer-readable media include program instructions toimplement various operations embodied by a computer. The media may alsoinclude, alone or in combination with the program instructions, datafiles, data structures, and the like. The media and program instructionsmay be those specially designed and constructed for the purposes of thepresent invention, or they may be of the kind well-known and availableto those having skill in the computer software arts. Examples ofcomputer-readable media include magnetic media such as hard disks,floppy disks, and magnetic tape; optical media such as CD ROM disks andDVD; magneto-optical media such as optical disks; and hardware devicesthat are specially configured to store and perform program instructions,such as read-only memory (ROM), random access memory (RAM), flashmemory, and the like. The media may also be a transmission medium suchas optical or metallic lines, wave guides, and so on, and is envisionedinclude a carrier wave transmitting signals specifying the programinstructions, data structures, and so on. The computer-readablerecording medium can also be distributed over network-coupled computersystems so that the computer-readable code is stored and executed in adistributed fashion. Examples of program instructions include bothmachine code, such as produced by a compiler, and files containinghigher level code that may be executed by the computer using aninterpreter. The described hardware devices may be configured to act asone or more software modules in order to perform the operations of theabove-described embodiments of the present invention.

Although exemplary embodiments of the present invention have beendisclosed for illustrative purposes, those skilled in the art willappreciate that various modifications, additions, and substitutions arepossible, without departing from the scope of the present invention.Therefore, the present invention is not limited to the above-describedembodiments, but is defined by the following claims, along with theirfull scope of equivalents.

We claim:
 1. A method of detecting and identifying arcing comprising:obtaining a plurality of line-current samples at a sampling rate over acycle of a voltage waveform; calculating a plurality of differencefunction values as a difference between two consecutive line-currentsamples of said plurality of line-current samples; determine a maximumvalue and a minimum value of said plurality of line current samples forthe cycle; calculating a peak-to-peak value of the line-current for thecycle as a relative difference between said maximum value and saidminimum value of said plurality of line current samples; calculating anaverage of the difference function values; first comparing each of thedifference function values to the calculated average of the differencefunction values for the cycle; second comparing each of the differencefunction values to the calculated peak-to-peak value of the line-currentfor the cycle; and identifying at least one fast transient current spikein the cycle based on a result of at least one of said first comparingand said second comparing.
 2. The method of claim 1, further comprising:computing a composite comparison function based on said first comparingand said second comparing to form a weighting function; and furtheridentifying at least one fast transient current spike in the cycle basedon said weighting function.
 3. The method of claim 2, wherein furthersaid weighing function performs at least one of: emphasizes differencefunction values that are large in comparison to the peak-to-peak valueof the line-current and to the average of the difference of the functionvalues; and de-emphasizes difference values that are small in comparisonto the peak-to-peak value of the line-current and to the average of thedifference of the function values.
 4. The method of claim 2, furthercomprising setting at least first and second thresholds to determine ifarcing is present within the cycle based on the computing of thecomposite comparison function.
 5. The method of claim 4, wherein thefirst threshold comprises a detection value limit above which the resultof the calculation for a given one of said line-current samples isrecognized as a current-spike, and the second threshold comprises aminimum required number of said line-current samples within the cyclefor which the result of the calculation exceeds a current-spikedetection value limit.
 6. The method of claim 5, wherein said firstthreshold is set such that noise present under no-load conditions doesnot produce any samples within a given cycle that are recognized as saidcurrent-spike, and said second threshold is set high enough toaccommodate normal operating conditions in which at least one of saidcurrent-spikes may be present.
 7. The method of claim 5, furthercomprising adjusting at least one of the first and second thresholds forperforming a determination of the presence of arcing within the cycle.8. The method of claim 1, wherein the first comparing is defined bywhere,${S_{2}( X_{n} )} = \frac{❘{X_{n} - X_{({n - 1})}}❘}{( \frac{1}{N - 1} ){\sum_{k = 2}^{N}( {❘{X_{k} - X_{({k - 1})}}❘} )}}$S₁(X_(n)) is the comparison result of the nth difference value to thepeak-to-peak value of the line-current, S₂(X_(n)) is the comparisonresult of the nth difference value to the average difference value,X_(n) is the nth sample of the obtained line-current samples X,X_((n-1)) is a sample preceding the nth sample of the obtainedline-current samples X, max(X) is the maximum value of the line-currentsamples obtained during the cycle, min(X) is the minimum value of theline-current samples obtained during the cycle, and N is the number ofline-current samples obtained during the cycle.
 9. The method of claim1, wherein the second comparing is defined by${S_{1}( X_{n} )} = \frac{❘{X_{n} - X_{({n - 1})}}❘}{\lbrack {{\max(X)} - {\min(X)}} \rbrack}$where, S₁(X_(n)) is the comparison result of the nth difference value tothe peak-to-peak value of the line-current, S₂(X_(n)) is the comparisonresult of the nth difference value to the average difference value,X_(n) is the nth sample of the obtained line-current samples X,X_((n-1)) is a sample preceding the nth sample of the obtainedline-current samples X, max(X) is the maximum value of the line-currentsamples obtained during the cycle, min(X) is the minimum value of theline-current samples obtained during the cycle, and N is the number ofline-current samples obtained during the cycle.
 10. The method of claim2, wherein the first comparing is defined by${{S_{2}( X_{n} )} = \frac{❘{X_{n} - X_{({n - 1})}}❘}{( \frac{1}{N - 1} ){\sum_{k = 2}^{N}( {❘{X_{k} - X_{({k - 1})}}❘} )}}},$the second comparing is defined by${{S_{1}( X_{n} )} = \begin{matrix}{❘{X_{n} - X_{({n - 1})}}❘} \\\lbrack {{\max(X)} - {\min(X)}} \rbrack\end{matrix}},$ and the computing of the composite comparison functionis defined byS ₃(X _(n))=S ₁(X _(n))*S ₂(X _(n)), where, S₁(X_(n)) is the comparisonresult of the nth difference value to the peak-to-peak value of theline-current, S₂(X_(n)) is the comparison result of the nth differencevalue to the average difference value, X_(n) is the nth sample of theobtained line-current samples X, X_((n-1)) is a sample preceding the nthsample of the obtained line-current samples X, max(X) is the maximumvalue of the line-current samples obtained during the cycle, min(X) isthe minimum value of the line-current samples obtained during the cycle,and N is the number of line-current samples obtained during the cycle.11. The system of claim 1, wherein the range classifications for arctest clearing times based on the current level being tested meet UL1699for the class of the circuit interrupter.